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  Method and apparatus for controlling autonomic computing system processes using knowledge-based reasoning mechanismsUSPTO Application #: 20080071714Title: Method and apparatus for controlling autonomic computing system processes using knowledge-based reasoning mechanisms Abstract: A system [100] is provided that includes a Model-Based Translation Layer [200] to accept an input event being formed in any of a pre-determined set of languages and protocols, and output an output message having a common language and protocol. The system [100] also includes a State Processing Layer [300] to (a) parse the output message to determine an event, an externally perceived state of the event, and an internally perceived state of the event; (b) determine a type of the event; (c) determine whether the externally perceived state of the event is substantially equivalent to the internally perceived state of the event; and (d) invoke policy control to lookup action functions to address the event in response to determining that a combination of the type of the event and the externally perceived state of the event is determined to be valid. (end of abstract)
Agent: Motorola, Inc. - Schaumburg, IL, US Inventors: Barry J. Menich, John C. Strassner USPTO Applicaton #: 20080071714 - Class: 706 45 (USPTO) The Patent Description & Claims data below is from USPTO Patent Application 20080071714. Brief Patent Description - Full Patent Description - Patent Application Claims
RELATED APPLICATIONS [0001]U.S. application Ser. No. 11/422,681 "AUTONOMIC COMPUTING METHOD AND APPARATUS" as was filed on Jun. 7, 2006 using attorney's docket number CML03322N; [0002]U.S. application Ser. No. 11/422,661 "METHOD AND APPARATUS FOR AUGMENTING DATA AND ACTIONS WITH SEMANTIC INFORMATION TO FACILITATE THE AUTONOMIC OPERATIONS OF COMPONENTS AND SYSTEMS" as was filed on Jun. 7, 2006 using attorney's docket number CML03000N; [0003]U.S. application Ser. No. 11/422,671 "PROBLEM SOLVING MECHANISM SELECTION FACILITATION APPARATUS AND METHOD" as was filed on Jun. 7, 2006 using attorney's docket number CML03124N; and [0004]U.S. application Ser. No. 11/422,642 "METHOD AND APPARATUS FOR harmonizing the gathering of data and issuing of commands in an autonomic computing system using model-based translation" as was filed on Jun. 7, 2006 using attorney's docket number CML02977N; [0005]wherein the contents of each of these related applications are incorporated herein by this reference. TECHNICAL FIELD [0006]This invention relates generally to the fields of network and element management, including different means to realize such systems (such as Web Services and grid services), and more particularly to the field of self-managing and self-governing (i.e., autonomic) computing systems. BACKGROUND [0007]Networks are often comprised of heterogeneous computing elements, each with their own distinct set of functions and approaches to providing commands and data regarding the operation of those functions. Elements may assume different roles and functions over time and in certain contexts, which in turn requires their configurations to vary. The problem is that even the same product from the same vendor introduces at least two types of problems. The first is that a product can run multiple versions of a device operating system. This illustrates the problem of introducing syntax and semantic changes in a relatively short timeframe (each successive upgrade) over the lifecycle of one or more products. A second example is that a single device can be programmed using different languages (for example, a vendor-proprietary as well as a standard language). This plays havoc with the control loop, as it is now difficult or most likely impossible to deduce which set of monitoring algorithms are used to ensure that a particular set of configuration commands are executed correctly. As a consequence, these computing elements may (and often do) have different, incompatible formats and languages for providing data and receiving commands. [0008]Currently, management elements are built in a custom/stovepipe fashion precisely because of the above limitations. This leads to solution robustness burdened by scalability problems. More importantly, it prohibits management systems from sharing and communicating decisions on similar data and commands. Hence, additional software must be built for each combination of management systems that need to communicate. [0009]Current systems use specific architectures that solve particular problems that constitute a subset of those requiring a solution to enable seamless mobility. Such computing systems do not, however, adequately support means to analyze the semantics involved in operations, administration and management (such as using machine learning or knowledge-based reasoning). Put another way, current computing systems build unique, point solutions for customers from a general-purpose toolset and are not focused on adaptive learning and reasoning frameworks. [0010]Arguably, an important focus of current and future systems is to enable a business to drive the services and resources of a network at any given point in time. Unfortunately, current systems do not provide a general approach that addresses terrestrial and wireless networking. Some autonomic systems have been proposed. However, the proposed systems do not address this problem either. For example, while research can posit the addition of a flexible set of simple machine learning tools that can be brought together to implement rule-reasoning, case-based reasoning, correlation engine functions, and some amount of data mining there are at least two general problems that emerge. First, these solutions do not generalize to causal explanation or inductive expectation. Second, these systems do not interact in any way with information models or ontologies, which have been identified as two mechanisms to provide semantic interoperability and inference. [0011]The ability of these current systems to increase the scope of learning and reasoning capabilities is hampered by being locked into the architectural requirement of custom-built software that provides sensing and command functions. These sensing and command functions are usually of fixed functionality, which exacerbates this problem. Furthermore, this software is embedded in managed elements and must either be changed to accommodate any changes in the learning and/or reasoning capabilities in the autonomic management element(s), or external mediation software must be developed to map the fixed functions embedded in a device into a set of information that manages the application. In addition to this, a further constraint is imposed by conformance to the Common Base Event ("CBE") standard. While the CBE provides some flexibility in supporting fields for "additional information," the utility of the approach is compromised by the limited number of event types supported. [0012]While these systems typically include the notions of "self-tuning" or "self-optimization" in their discussions regarding autonomic computing, they have no support for characterizing system operation as a basis for comparison to serve the optimization or tuning processes. Furthermore, there is no concept of a "universal knowledge base," nor is there a concept of a common set of reasoning mechanisms that can be used to make decisions. Finally, there is no ability to incorporate new knowledge. [0013]Various companies currently vend analysis and decision-making software into the telecommunications and data communications Operation Support Systems (OSS) and Business Support Systems (BSS) markets. Typically, these solutions focus on a particular aspect of analysis and/or decision-making, and always strive to improve the "quality of view" in the system. This last point is crucial in supporting the human-in-the-loop aspect of current system management techniques. Data mining, correlation engines, expert systems, and case-based reasoning all have best-in-class examples of point solution implementations. One example of a current system has combined a case-based reasoning case indexing scheme with utility functions (decision making). In addition, there are many approaches that integrate correlation engines or data mining with rule or case-based systems. None of these solutions, however, provide a general purpose framework, and none of them integrate multiple reasoning and learning techniques. BRIEF DESCRIPTION OF THE DRAWINGS [0014]The accompanying figures, where like reference numerals refer to identical or functionally similar elements throughout the separate views and which together with the detailed description below are incorporated in and form part of the specification, serve to further illustrate various embodiments and to explain various principles and advantages all in accordance with the present invention. [0015]FIG. 1 illustrates a conceptual block diagram of an autonomic system based on using the Directory Enabled Network-next generation ("DEN-ng") model according to at least one embodiment of the invention; [0016]FIG. 2 illustrates a Model Based Translation Layer ("MBTL") according to at least one embodiment of the invention; [0017]FIG. 3 illustrates the MBLT and a State Processing Layer ("SPL") according to at least one embodiment of the invention; [0018]FIG. 4 illustrates a first portion of a process flow of the SPL according to at least one embodiment of the invention; [0019]FIG. 5 illustrates a second portion of a process flow of the SPL according to at least one embodiment of the invention; [0020]FIG. 6 illustrates a third portion of a process flow of the SPL according to at least one embodiment of the invention; Continue reading... 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